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HomeHomework HelpstatisticsPositive Correlation

Positive Correlation

A positive correlation is a statistical relationship between two variables in which an increase in one variable is associated with an increase in the other variable. This indicates that as one variable rises, the other tends to rise as well, suggesting a direct relationship.

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Overview

Positive correlation is a fundamental concept in statistics that describes a relationship between two variables where both increase together. Understanding this concept is crucial for analyzing data in various fields, including economics, health, and social sciences. By learning how to calculate and...

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Key Terms

Variable
A factor that can change in an experiment or analysis.

Example: Height and weight are variables in a health study.

Correlation
A statistical measure that describes the extent to which two variables change together.

Example: There is a correlation between study time and exam scores.

Correlation Coefficient
A numerical value that ranges from -1 to 1, indicating the strength and direction of a correlation.

Example: A correlation coefficient of 0.8 indicates a strong positive correlation.

Scatter Plot
A graph that uses dots to represent the values of two different variables.

Example: A scatter plot can show the relationship between hours studied and test scores.

Trend Line
A line that best represents the data on a scatter plot, indicating the direction of the relationship.

Example: A trend line can show a positive slope, indicating positive correlation.

Causation
The action of causing something; a relationship where one event causes another.

Example: Smoking causes an increase in lung cancer risk.

Related Topics

Negative Correlation
A relationship where one variable increases while the other decreases.
intermediate
Linear Regression
A statistical method for modeling the relationship between a dependent variable and one or more independent variables.
advanced
Statistical Significance
A measure of whether the results of a study are likely due to chance or reflect a true effect.
intermediate

Key Concepts

variablescorrelation coefficientlinear relationshipdata analysis